Automatic diagnosis for prostate cancer using run-length matrix method

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 7260, Issue , 2009, Pages

  Sun, Xiaoyan ^a   Chuanga, Shao Hui ^a   Li, Jiang ^a   McKenzie, Frederic ^a  

^a Old Dominion University ^*  (United States)

Author keywords

CAD development; Histopathology; Prostate cancer; Texture analysis

Indexed keywords

AUTOMATIC CLASSIFICATION; AUTOMATIC DIAGNOSIS; BIOPSY SAMPLES; CAD DEVELOPMENT; CLASSIFICATION ACCURACY; CROSS VALIDATION; DIGITIZED IMAGES; FEATURE SELECTION ALGORITHM; GRAY-LEVEL; HISTOLOGICAL IMAGES; HISTOPATHOLOGICAL IMAGES; HISTOPATHOLOGY; MATRIX; MATRIX METHODS; MULTI LAYER PERCEPTRON; NORMAL TISSUE; PIXEL INTENSITIES; PROSTATE CANCER; PROSTATE CANCERS; PROSTATE SPECIFIC ANTIGEN; PROSTATIC CARCINOMA; QUANTITATIVE ASSESSMENTS; RADICAL PROSTATECTOMY; RUN LENGTH; SENSITIVITY AND SPECIFICITY; STANDARD DEVIATION; SUB-REGION; SUB-REGIONS; TEXTURE ANALYSIS; TEXTURE ANALYSIS METHOD; TEXTURE FEATURES; TISSUE ABNORMALITIES; TISSUE SAMPLES;

AUTOMATIC INDEXING; BIOLOGICAL RADIATION EFFECTS; HISTOLOGY; MEDICAL IMAGING; PIXELS; TEXTURES;

COMPUTER AIDED DIAGNOSIS;

EID: 66749130272     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.811414     Document Type: Conference Paper

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